Integ In s Can

Downlo cer vaccine feasibility would benefit from reducing the number and duration of vaccinations without ishing efficacy. However, the duration of in vivo studies and the huge number of possible variations cination protocols have discouraged their optimization. In this study, we employed an established model of preventive vaccination using HER-2/neu transgenic mice (BALB-neuT) to validate o–designed protocols that reduce the number of vaccinations and optimize efficacy. With biological g, the in silico model captured the overall in vivo behavior and highlighted certain critical issues. although vaccinations could be reduced in number without sacrificing efficacy, the intensity of early ations was a key determinant of long-term tumor prevention needed for predictive utility in the . Second, after vaccinations ended, older mice exhibited more rapid tumor onset and sharper decline ibody levels than young mice, emphasizing immune aging as a key variable in models of vaccine ols for elderly individuals. Long-term studies confirmed predictions of in silico modeling in which an ne plateau phase, once reached, could be maintained with a reduced number of vaccinations. Furore, that rapid priming in young mice is required for long-term antitumor protection, and that the cy of mathematical modeling of early immune responses is critical. Finally, that the design and ing of cancer vaccines and vaccination protocols must take into account the progressive aging of mune system, by striving to boost immune responses in elderly hosts. Our results show that an the im integrated in vivo–in silico approach could improve both mathematical and biological models of cancer immunoprevention. Cancer Res; 70(20); 7755–63. ©2010 AACR.